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| Criterion |  Operations Fishbone Diagram |  Product Discovery Smoke Test |  Operations Root Cause Analysis |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | When a problem has several possible contributing factors, the method sorts causes by cause areas. It prevents an initial hunch from blocking the view of other plausible drivers. | When demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. | When a problem keeps recurring and the cause stays unclear, the method exposes the underlying mechanism. It separates symptom, guess, and robust explanation from one another. | When two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects. |
Complexitydifferent | Low | Low | Medium | High |
Timedifferent | 30-60 min | 1-5 Tage | 1-4 h | 1-4 Wochen |
Participantsdifferent | 2-8 | Nutzertraffic | 3-8 | 1-6 |
Formatdifferent | Workshop | Async | Workshop + async | Async |
Outputdifferent | Fishbone Diagram, Cause Categories, Investigation Backlog | Interest Metrics, Conversion Signal, Learning Note | Problem Statement, Cause Hypotheses, Confirmed Causes, Action Plan | Experiment results, Decision log, Learning summary |
Tagsno overlap | Root causeQualityOperations | ValidationExperimentsDemandGrowth | Root causeProblem solvingQualityIncident | ExperimentsGrowthAnalyticsValidation |